Using Economics and Epidemiology to Evaluate MRSA Decolonization in the VA Anticipated Impact on Veteran's Health Care By examining the associations between facility-level decolonization usage and MRSA infection rates, as well as the impact of MRSA infections on length of inpatient stay and post-discharge costs, we will provide valuable insight into the specific question of whether to add decolonization to the VA-wide initiative aimed at controlling Methicillin-resistant Staphylococcus aureus (MRSA) infections within VA hospitals. Through this research and training experience, I will be prepared to conduct similar research in other healthcare-acquired and community-acquired infections that could impact infection control practice throughout the VA healthcare system. Project Background Treatments for infectious diseases are unique in that they produce externalities, spillover effects that are felt by individuals who are currently not infected. While these externalities are recognized, their magnitude is not well measured. Similarly, the impact of nosocomial infections on health care cost and utilization has not been quantified accurately. These two elements (externalities and costs) are important inputs to an economic analysis of any infectious disease treatment strategy. Project Objectives The goal of this research is to apply cutting edge empirical methods of estimating the costs and benefits of prevention efforts for infectious disease transmission to the specific case of decolonization of MRSA within the VA. This research has 3 aims: (1) quantify the positive externalities associated with decolonization of MRSA positive veterans, (2) estimate the cost and healthcare use associated with hospital-acquired MRSA infections in the VA, and (3) perform economic analyses of a MRSA strategy that adds decolonization to the VA's current VA strategy of contact isolation. Methods In Aim (1), we will use a nationwide database of VA patient data obtained from Patient Care Services (PCS) to estimate the association between hospital-level decolonization use and resistance to this decolonization and the risk of hospital-acquired MRSA infection using multi- level logistic regressions. Next we will link this PCS data to VA Decision Support System (DSS) data to estimate the impact of MRSA infection on inpatient length of stay using inverse probability weights in a longitudinal logistic regression and on post-discharge health care costs and utilization using generalized linear models that are appropriate for skewed data, in Aim (2). In addition, we will link this PCS and DSS data to Medicare and VA Fee Basis data to capture post-discharge health care costs from outside the VA. Finally, in Aim (3), we will use the results for Aims (1) and (2) as inputs to an agent-based model of MRSA transmission to conduct dynamic economic analyses.